'Pandas read_csv - dealing with columns that have ID numbers with consecutive '$' and '#' symbols, along with letters and digits
I'm trying to read a csv file with a column of data that has a scrambled ID number that includes the occasional consecutive $$ along with #, numbers, and letters.
| SCRAMBLE_ID |
|---|
| AL9LLL677 |
| AL9$AM657 |
| $L9$$4440 |
| #L9$306A1 |
etc.
I tried the following:
df = pd.read_csv('MASTER~1.CSV',
dtype = {'SCRAMBLE_ID': str})
which rendered the third entry as L9$4440 (L9 appear in serif font, italicized, and the first and second $ vanish).
Faced with an entire column of ID numbers configured in this manner, what is the best way of dealing with such data? I can imagine:
- PRIOR TO pd.read_csv: replacing the offending symbols with substitutes that don't create this problem (and what would those be), OR,
- is there a way of preserving the IDs as is but making them into a data type that ignores these symbols while keeping them present?
Thank you. I've attached a screenshot of the .csv side by side with resulting df (Jupyter notebook) below.
csv column to pandas df with $$
Sources
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